Distributed temperature sensing (DTS) devices are optoelectronic devices which measure temperature by optical fibers functioning as linear sensors. Temperature values are recorded along the optical sensor cable as a continuous profile. A high accuracy of temperature determination is achieved over long distances. Measurement distances of several kilometers can be achieved. The temperature dependence of the Raman effect can be used for a DTS measurement.
In Raman-DTS, the Stokes and Antistokes backscatter from a medium (like an optical fiber) are both measured. They differ in wavelength so that suitable filters separate both. They may be measured for instance by two detectors (one for the Stokes signal and one for the Antistokes signal) or one detector in a sequence (where the detector is switched either to the Stokes signal or to the Antistokes signal). The temperature is then calculated from their ratio. The Antistokes data and the Stokes data have different relative sensitivities (i.e. the relative change per degree Celsius temperature change) so that the ratio also bears the temperature information. The ratio operating has the advantage that losses of Stokes and Antistokes in the path cancel out (at least as far as it is the same for both), for instance connector losses or by attenuation in the fiber over distance. Remaining differences (that do not cancel out) can be compensated to some degree by different methods like dual-ended measurement (measuring the same medium from opposite directions), measurement with two different incident wavelength of suitable wavelength difference and using for example Stokes from the one wavelength and Antistokes from the other wavelength, or by supplying information about loss differences between Stokes and Antistokes medium (for instance by a number in dB/km).
Both, Stokes and Antistokes data from the measurement bear some noise for instance from a photodetector (for instance thermal noise or shot noise) and the following electronics and digitizer. A drawback of the ratio calculation is that both, the noise in Stokes as well as the noise in Antistokes contribute to the noise in the ratio data. From statistics it follows that in combination they lead to higher noise in the ratio data than would be in the ideal or hypothetic case that any of them would be noise-free.
As noise limits accuracy of distributed sensing, it is generally desired to reduce it. Moreover, noise and other distortions in the measurement data of a distributed sensing device may result in an inaccuracy of the physical quantity to be determined.
There may be a need to enable determining a physical quantity by distributed sensing with high accuracy.